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Journal of Proteome Research Jun 2024Gut microbiota-derived microbial compounds may link to the pathogenesis of colorectal cancer (CRC). However, the role of the host-microbiome in the incidence and...
Gut microbiota-derived microbial compounds may link to the pathogenesis of colorectal cancer (CRC). However, the role of the host-microbiome in the incidence and progression of CRC remains elusive. We performed 16S rRNA sequencing, metabolomics, and proteomic studies on samples from 85 CRC patients who underwent colonoscopy examination and found two distinct changed patterns of microbiome in CRC patients. The relative abundances of and continuously increased from intramucosal carcinoma to advanced stages, whereas , , , , , and were significantly altered only in intermediate lesions. Fecal metabolomics analysis exhibited consistent increases in bile acids, indoles, and urobilin as well as a decrease in heme. Serum metabolomics uncovered the highest levels of bilin, glycerides, and nucleosides together with the lowest levels of bile acids and amino acids in the stage of intermediate lesions. Three fecal and one serum dipeptides were elevated in the intermediate lesions. Proteomics analysis of colorectal tissues showed that oxidation and autophagy through the PI3K/Akt-mTOR signaling pathway contribute to the development of CRC. Diagnostic analysis showed multiomics features have good predictive capability, with AUC greater than 0.85. Our overall findings revealed new candidate biomarkers for CRC, with potentially significant diagnostic and prognostic capabilities.
Topics: Humans; Colorectal Neoplasms; Proteomics; Gastrointestinal Microbiome; Feces; Metabolomics; Male; RNA, Ribosomal, 16S; Female; Middle Aged; Aged; Signal Transduction; Biomarkers, Tumor; Multiomics
PubMed: 38634357
DOI: 10.1021/acs.jproteome.3c00894 -
Journal of Periodontal Research Oct 2023To investigate the existence of any association between new putative periodontal pathogens and periodontitis. Two independent reviewers conducted electronic literature... (Meta-Analysis)
Meta-Analysis Review
To investigate the existence of any association between new putative periodontal pathogens and periodontitis. Two independent reviewers conducted electronic literature searches in the MEDLINE (PubMed), EMBASE, DOSS and Google Scholar databases as well as a manual search to identify eligible clinical studies prior to November 2022. Studies comparing the prevalence of microorganisms other than the already-known periodontal pathogens in subgingival plaque and/or saliva samples between subjects with periodontitis and subject with periodontal health were included. Meta-analyses were performed on data provided by the included studies. Fifty studies including a total of 2739 periodontitis subjects and 1747 subjects with periodontal health were included. The Archaea domain and 25 bacterial species (Anaeroglobus geminatus, Bacteroidales [G-2] bacterium HMT 274, Desulfobulbus sp. HMT 041, Dialister invisus, Dialister pneumosintes, Eubacterium brachy, Enterococcus faecalis, Eubacterium nodatum, Eubacterium saphenum, Filifactor alocis, Fretibacterium sp. HMT 360, Fretibacterium sp. HMT 362, Mogibacterium timidum, Peptoniphilaceae sp. HMT 113, Peptostreptococcus stomatis, Porphyromonas endodontalis, Slackia exigua, Streptococcus gordonii, Selenomonas sputigena, Treponema amylovorum, Treponema lecithinolyticum, Treponema maltophilum, Treponema medium, Treponema parvum and Treponema socranskii) were found to be statistically significantly associated with periodontitis. Network studies should be conducted to investigate the role of these newly identified periodontitis-associated microorganisms through interspecies interaction and host-microbe crosstalk analyses.
Topics: Humans; Bacteria; Periodontitis; Dental Plaque; Bacteroides; Eubacterium
PubMed: 37572051
DOI: 10.1111/jre.13173 -
Frontiers in Cellular and Infection... 2023Oral microbiota is closely related to the homeostasis of the oral cavity and lungs. To provide potential information for the prediction, screening, and treatment...
BACKGROUND
Oral microbiota is closely related to the homeostasis of the oral cavity and lungs. To provide potential information for the prediction, screening, and treatment strategies of individuals, this study compared and investigated the bacterial signatures in periodontitis and chronic obstructive pulmonary disease (COPD).
MATERIALS AND METHODS
We collected subgingival plaque and gingival crevicular fluid samples from 112 individuals (31 healthy controls, 24 patients with periodontitis, 28 patients with COPD, and 29 patients with both periodontitis and COPD). The oral microbiota was analyzed using 16S rRNA gene sequencing and diversity and functional prediction analysis were performed.
RESULTS
We observed higher bacterial richness in individuals with periodontitis in both types of oral samples. Using LEfSe and DESeq2 analyses, we found differentially abundant genera that may be potential biomarkers for each group. is the predominant genus in COPD. Ten genera, including , , and were predominant in periodontitis. and were the signature of the healthy controls. The significantly different pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) between healthy controls and other groups were concentrated in genetic information processing, translation, replication and repair, and metabolism of cofactors and vitamins.
CONCLUSIONS
We found the significant differences in the bacterial community and functional characterization of oral microbiota in periodontitis, COPD and comorbid diseases. Compared to gingival crevicular fluid, subgingival plaque may be more appropriate for reflecting the difference of subgingival microbiota in periodontitis patients with COPD. These results may provide potentials for predicting, screening, and treatment strategies for individuals with periodontitis and COPD.
Topics: Humans; Dysbiosis; RNA, Ribosomal, 16S; Periodontitis; Bacteria; Pulmonary Disease, Chronic Obstructive; Chronic Periodontitis
PubMed: 36844402
DOI: 10.3389/fcimb.2023.1121399 -
Frontiers in Veterinary Science 2023The gut microbiomes of equine are plentiful and intricate, which plays an important part in the growth. However, there is a relative lack of information on the microbial...
INTRODUCTION
The gut microbiomes of equine are plentiful and intricate, which plays an important part in the growth. However, there is a relative lack of information on the microbial diversity in the pony's gut.
METHODS
In this article, 118 fecal samples from DeBa pony, NiQi pony and GuZh horse were studied by 16S rRNA amplicon sequencing.
RESULTS
Diversity analysis was used to determine the difference of gut microbiota composition among different breeds. Alpha diversity analysis showed that the gut microbiota of NiQi ponies were abundant and various. Beta diversity analysis showed that the microorganisms constitution of DeBa ponies was more similar to that of NiQi ponies. LDA Effect Size (LEfSe) analysis result that the microorganism biomarkers for NiQi pony at the genus level were Phascolarctobacterium, Paludibacter, and Fibrobacter; the bacterial biomarker for DeBa pony was Streptococcus and Prevotella; and the bacterial biomarkers for GuZh horses was Treponema, Treponema Mogibacterium, Adlercreutzia, and Blautia. The correlation analysis between genera with >1% abundance and horse height found that Streptococcus ( < 0.01), Treponema ( < 0.01), Coprococcus ( < 0.01), Prevotella ( < 0.01), Phascolarctobacterium ( < 0.01), and Mogibacterium ( < 0.01) were significantly associated with horses' height. The functional prediction results indicated that DeBa pony have a microbiota functional more similar to NiQi pony.
DISCUSSION
For the first time, our results announce the species composition and structure of the gut microbiota in Chinese ponies. At the same time, our results can provide theoretical reference for further understanding the healthy breeding, feeding management and disease prevention of horses.
PubMed: 36777669
DOI: 10.3389/fvets.2023.1102186 -
Journal of Clinical Periodontology Nov 2023Since blood metabolomic profiles of obese individuals are known to be altered, our objective was to examine the association between obesity-related metabolic patterns...
AIM
Since blood metabolomic profiles of obese individuals are known to be altered, our objective was to examine the association between obesity-related metabolic patterns and subgingival microbial compositions in obese and non-obese periodontally healthy individuals.
MATERIALS AND METHODS
Thirty-nine periodontally healthy subjects were enrolled. Based on body mass index scores, 20 subjects were categorized as lean and 19 as obese. A comprehensive periodontal examination was performed. Subgingival plaque and blood samples were collected. Plaque samples were analysed for bacteria using 16S rDNA sequencing. Untargeted metabolomic profiling (mass spectrometry) was used to quantify metabolites in serum.
RESULTS
Obese subjects were statistically associated with several periodontopathic taxa including Dialister invisus, Prevotella intermedia, Prevotella denticola, Fusobacterium nucleatum_subsp.vincentii, Mogibacterium diversum, Parvimonas micra and Shuttleworthia satelles. In obese individuals, an amino acid-related metabolic pattern was elevated; however, there was a decrease in metabolic patterns related to lipids and cofactor/vitamins. These metabolic perturbations were associated with multiple subgingival bacterial species that differentiated lean from obese individuals.
CONCLUSIONS
Obesity-related perturbations in circulating blood metabolites are associated with the development of periodontopathic bacterial colonization in the subgingival microbiome and consequently may increase the risk for periodontal disease in obese individuals.
PubMed: 37536958
DOI: 10.1111/jcpe.13860 -
Journal of Oral Microbiology Nov 2020: Refractory infection is an important factor affecting the progression of medication-related osteonecrosis of the jaw (MRONJ) from clinical stage I to stage II/III. The...
: Refractory infection is an important factor affecting the progression of medication-related osteonecrosis of the jaw (MRONJ) from clinical stage I to stage II/III. The aim of this study was to explore the distribution of bacteria and their association with the inflammatory pathway of stage II/III MRONJ. : Nine specimens of fresh inflammation tissue, located next to the necrotic bone or sequestrum, were collected from MRONJ patients. Nine specimens from normal oral mucosa were collected from healthy patients. The 16S rRNA gene sequencing method was used to determine the distribution characteristics of the bacterial colony. The protein microarray analysis was used to detect the expression of inflammatory cytokines. : The average relative abundance of , and was higher, while and were lower in the MRONJ group. Most pro-inflammatory cytokines were up-regulated in the MRONJ group; yet, only IFNγ, TNFα, and IL8 showed statistical differences ( < 0.05). and were positively correlated with IL8, and was positively correlated with IFNγ and TNFα. : IL8/IFNγ/TNFα pro-inflammatory effect caused by , and may be the leading cause of advancing MRONJ and thus may be used as a new target for infection control.
PubMed: 33391627
DOI: 10.1080/20002297.2020.1851112 -
PloS One 2024Osteomyelitis of the jaw is a severe inflammatory disorder that affects bones, and it is categorized into two main types: chronic bacterial and nonbacterial...
Osteomyelitis of the jaw is a severe inflammatory disorder that affects bones, and it is categorized into two main types: chronic bacterial and nonbacterial osteomyelitis. Although previous studies have investigated the association between these diseases and the oral microbiome, the specific taxa associated with each disease remain unknown. In this study, we conducted shotgun metagenome sequencing (≥10 Gb from ≥66,395,670 reads per sample) of bulk DNA extracted from saliva obtained from patients with chronic bacterial osteomyelitis (N = 5) and chronic nonbacterial osteomyelitis (N = 10). We then compared the taxonomic composition of the metagenome in terms of both taxonomic and sequence abundances with that of healthy controls (N = 5). Taxonomic profiling revealed a statistically significant increase in both the taxonomic and sequence abundance of Mogibacterium in cases of chronic bacterial osteomyelitis; however, such enrichment was not observed in chronic nonbacterial osteomyelitis. We also compared a previously reported core saliva microbiome (59 genera) with our data and found that out of the 74 genera detected in this study, 47 (including Mogibacterium) were not included in the previous meta-analysis. Additionally, we analyzed a core-genome tree of Mogibacterium from chronic bacterial osteomyelitis and healthy control samples along with a reference complete genome and found that Mogibacterium from both groups was indistinguishable at the core-genome and pan-genome levels. Although limited by the small sample size, our study provides novel evidence of a significant increase in Mogibacterium abundance in the chronic bacterial osteomyelitis group. Moreover, our study presents a comparative analysis of the taxonomic and sequence abundances of all genera detected using deep salivary shotgun metagenome data. The distinct enrichment of Mogibacterium suggests its potential as a marker to distinguish between patients with chronic nonbacterial osteomyelitis and chronic bacterial osteomyelitis, particularly at the early stages when differences are unclear.
Topics: Humans; Saliva; Osteomyelitis; Female; Microbiota; Male; Middle Aged; Metagenomics; Chronic Disease; Adult; Metagenome; Aged
PubMed: 38709734
DOI: 10.1371/journal.pone.0302569 -
JDR Clinical and Translational Research Jul 2024Common oral diseases are known to be associated with dysbiotic shifts in the supragingival microbiome, yet most oral microbiome associations with clinical end points...
INTRODUCTION
Common oral diseases are known to be associated with dysbiotic shifts in the supragingival microbiome, yet most oral microbiome associations with clinical end points emanate from cross-sectional studies. Orthodontic treatment is an elective procedure that can be exploited to prospectively examine clinically relevant longitudinal changes in the composition and function of the supragingival microbiome.
METHODS
A longitudinal cohort study was conducted among 24 adolescent orthodontic patients who underwent saliva and plaque sampling and clinical examinations at time points: before fixed appliance bonding and at 1, 6, and 12 wk thereafter. Clinical indices included bleeding on probing (BOP), mean gingival index (GI), probing depths (PDs), and plaque index (PI). To study the biologically (i.e., transcriptionally) active microbial communities, RNA was extracted from plaque and saliva for RNA sequencing and microbiome bioinformatics analysis. Longitudinal changes in microbiome beta diversity were examined using PERMANOVA tests, and the relative abundance of microbial taxa was measured using Kruskal-Wallis tests, Wilcoxon rank-sum tests, and negative binomial and zero-inflated mixed models.
RESULTS
Clinical measures of oral health deteriorated over time-the proportion of sites with GI and PI ≥1 increased by over 70% between prebonding and 12 wk postbonding while the proportion of sites with PD ≥4 mm increased 2.5-fold. , a health-associated species that antagonizes cariogenic pathogens, showed a lasting decrease in relative abundance during orthodontic treatment. Contrarily, caries- and periodontal disease-associated taxa, including , , and , increased in abundance after bonding. Relative abundances of and in prebonding saliva predicted elevated BOP 12 wk postbonding, whereas was associated with lower BOP.
CONCLUSIONS
This study offers insights into longitudinal community and species-specific changes in the supragingival microbiome transcriptome during fixed orthodontic treatment, advancing our understanding of microbial dysbioses and identifying targets of future health-promoting clinical investigations.
KNOWLEDGE TRANSFER STATEMENT
Bonding braces was associated with subsequent changes in the oral microbiome characterized by increases in disease-associated species, decreases in health-associated species, and worsened clinical measures of oral health.
Topics: Humans; Longitudinal Studies; Adolescent; Male; Biofilms; Female; Microbiota; Saliva; Transcriptome; Dental Plaque; Orthodontics; Gingiva; Child
PubMed: 37876206
DOI: 10.1177/23800844231199393 -
Frontiers in Cellular and Infection... 2022The combination of maxillofacial infections (MI) with descending necrotizing mediastinitis (DNM) is a complex disease characterized by rapid development and high...
The combination of maxillofacial infections (MI) with descending necrotizing mediastinitis (DNM) is a complex disease characterized by rapid development and high mortality. Here, we performed metagenomic next-generation sequencing (mNGS) using samples from 21 patients with MI and eight patients with DNM. In this study, we found that the species richness of the DNM group was higher than that of the MI group, and the species diversity of the DNM group was higher than that of the MI group, with no statistically significant differences between groups (P > 0.05). LefSE analysis revealed that the main species differing between groups were , , , and ( and ). In addition, the PLS-DA analysis revealed that the dominant groups in the DNM group at the species level were , , , , , and . Next, we correlated the clinical characteristics of the patients with the relative abundance of the pathogens identified in the LefSe and PLS-DA analyses. The relative abundance of was positively correlated with C-reactive protein (CRP) and calcitoninogen (PCT) but negatively correlated with the percentage of lymphocytes (Lymph%) (P < 0.05). On the other hand, was positively correlated with the percentage of neutrophils (Neut%) and glycated hemoglobin (GLU) (P < 0.05), and was positively correlated with CRP (P < 0.05).
Topics: Eubacterium; Humans; Mediastinitis; Streptococcus
PubMed: 35755831
DOI: 10.3389/fcimb.2022.873161 -
Journal of Dental Research Mar 2022An intuitive, clinically relevant index of microbial dysbiosis as a summary statistic of subgingival microbiome profiles is needed. Here, we describe a subgingival...
An intuitive, clinically relevant index of microbial dysbiosis as a summary statistic of subgingival microbiome profiles is needed. Here, we describe a subgingival microbial dysbiosis index (SMDI) based on machine learning analysis of published periodontitis/health 16S microbiome data. The raw sequencing data, split into training and test sets, were quality filtered, taxonomically assigned to the species level, and centered log-ratio transformed. The training data set was subject to random forest analysis to identify discriminating species (DS) between periodontitis and health. DS lists, compiled by various "Gini" importance score cutoffs, were used to compute the SMDI for samples in the training and test data sets as the mean centered log-ratio abundance of periodontitis-associated species subtracted by that of health-associated ones. Diagnostic accuracy was assessed with receiver operating characteristic analysis. An SMDI based on 49 DS provided the highest accuracy with areas under the curve of 0.96 and 0.92 in the training and test data sets, respectively, and ranged from -6 (most normobiotic) to 5 (most dysbiotic) with a value around zero discriminating most of the periodontitis and healthy samples. The top periodontitis-associated DS were spp., and , while and were the top health-associated DS. The index was highly reproducible by hypervariable region. Applying the index to additional test data sets in which nitrate had been used to modulate the microbiome demonstrated that nitrate has dysbiosis-lowering properties in vitro and in vivo. Finally, 3 genera (, and ) were identified that could be used for calculation of a simplified SMDI with comparable accuracy. In conclusion, we have developed a nonbiased, reproducible, and easy-to-interpret index that can be used to identify patients/sites at risk of periodontitis, to assess the microbial response to treatment, and, importantly, as a quantitative tool in microbiome modulation studies.
Topics: Dysbiosis; Humans; Microbiota; Periodontitis; RNA, Ribosomal, 16S; Treponema denticola
PubMed: 34428955
DOI: 10.1177/00220345211035775